Apolipoprotein(a) inhibits hepatitis C virus entry through interaction with infectious particles
Bibliographic record
Abstract
The development of different cell culture models has greatly contributed to increased understanding of the hepatitis C virus (HCV) life cycle. However, it is still challenging to grow HCV clinical isolates in cell culture. If overcome, this would open new perspectives to study HCV biology, including drug‐resistant variants emerging with new antiviral therapies. In this study we hypothesized that this hurdle could be due to the presence of inhibitory factors in patient serum. Combining polyethylene glycol precipitation, iodixanol gradient, and size‐exclusion chromatography, we obtained from HCV‐seronegative sera a purified fraction enriched in inhibitory factors. Mass spectrometric analysis identified apolipoprotein(a) (apo[a]) as a potential inhibitor of HCV entry. Apo(a) consists of 10 kringle IV domains (KIVs), one kringle V domain, and an inactive protease domain. The 10 KIVs are present in a single copy with the exception of KIV type 2 (KIV 2 ), which is encoded in a variable number of tandemly repeated copies, giving rise to numerous apo(a) size isoforms. In addition, apo(a) covalently links to the apolipoprotein B component of a low‐density lipoprotein through a disulfide bridge to form lipoprotein(a). Using a recombinant virus derived from the JFH1 strain, we confirmed that plasma‐derived and recombinant lipoprotein(a) as well as purified recombinant apo(a) variants were able to specifically inhibit HCV by interacting with infectious particles. Our results also suggest that small isoforms are less inhibitory than the large ones. Finally, we observed that the lipoprotein moiety of HCV lipoviroparticles was essential for inhibition, whereas functional lysine‐binding sites in KIV 7 , KIV 8 , and KIV 10 were not required. Conclusions : Our results identify apo(a) as an additional component of the lipid metabolism modulating HCV infection. (H epatology 2017;65:1851‐1864)
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".